Java tutorial
/* * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. The ASF licenses this file * to you under the Apache License, Version 2.0 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, * software distributed under the License is distributed on an * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY * KIND, either express or implied. See the License for the * specific language governing permissions and limitations * under the License. */ package org.apache.sysml.runtime.controlprogram.parfor; import java.io.IOException; import java.util.ArrayList; import java.util.HashMap; import java.util.List; import org.apache.commons.logging.Log; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.io.Writable; import org.apache.hadoop.mapred.JobConf; import org.apache.hadoop.mapred.OutputCollector; import org.apache.hadoop.mapred.Reporter; import scala.Tuple2; import org.apache.sysml.api.DMLScript; import org.apache.sysml.conf.ConfigurationManager; import org.apache.sysml.parser.Expression.DataType; import org.apache.sysml.runtime.DMLRuntimeException; import org.apache.sysml.runtime.controlprogram.LocalVariableMap; import org.apache.sysml.runtime.controlprogram.ParForProgramBlock; import org.apache.sysml.runtime.controlprogram.caching.CacheStatistics; import org.apache.sysml.runtime.controlprogram.caching.CacheableData; import org.apache.sysml.runtime.controlprogram.caching.MatrixObject; import org.apache.sysml.runtime.controlprogram.parfor.stat.InfrastructureAnalyzer; import org.apache.sysml.runtime.controlprogram.parfor.stat.Stat; import org.apache.sysml.runtime.instructions.cp.Data; import org.apache.sysml.runtime.util.LocalFileUtils; import org.apache.sysml.utils.Statistics; /** * Common functionalities for parfor workers in MR jobs. Used by worker wrappers in * mappers (base RemoteParFor) and reducers (fused data partitioning and parfor) * */ public class RemoteParForUtils { public static void incrementParForMRCounters(Reporter reporter, long deltaTasks, long deltaIterations) { //report parfor counters if (deltaTasks > 0) reporter.incrCounter(ParForProgramBlock.PARFOR_COUNTER_GROUP_NAME, Stat.PARFOR_NUMTASKS.toString(), deltaTasks); if (deltaIterations > 0) reporter.incrCounter(ParForProgramBlock.PARFOR_COUNTER_GROUP_NAME, Stat.PARFOR_NUMITERS.toString(), deltaIterations); JobConf job = ConfigurationManager.getCachedJobConf(); if (DMLScript.STATISTICS && !InfrastructureAnalyzer.isLocalMode(job)) { //report cache statistics reporter.incrCounter(ParForProgramBlock.PARFOR_COUNTER_GROUP_NAME, Stat.PARFOR_JITCOMPILE.toString(), Statistics.getJITCompileTime()); reporter.incrCounter(ParForProgramBlock.PARFOR_COUNTER_GROUP_NAME, Stat.PARFOR_JVMGC_COUNT.toString(), Statistics.getJVMgcCount()); reporter.incrCounter(ParForProgramBlock.PARFOR_COUNTER_GROUP_NAME, Stat.PARFOR_JVMGC_TIME.toString(), Statistics.getJVMgcTime()); reporter.incrCounter(CacheableData.CACHING_COUNTER_GROUP_NAME, CacheStatistics.Stat.CACHE_HITS_MEM.toString(), CacheStatistics.getMemHits()); reporter.incrCounter(CacheableData.CACHING_COUNTER_GROUP_NAME, CacheStatistics.Stat.CACHE_HITS_FSBUFF.toString(), CacheStatistics.getFSBuffHits()); reporter.incrCounter(CacheableData.CACHING_COUNTER_GROUP_NAME, CacheStatistics.Stat.CACHE_HITS_FS.toString(), CacheStatistics.getFSHits()); reporter.incrCounter(CacheableData.CACHING_COUNTER_GROUP_NAME, CacheStatistics.Stat.CACHE_HITS_HDFS.toString(), CacheStatistics.getHDFSHits()); reporter.incrCounter(CacheableData.CACHING_COUNTER_GROUP_NAME, CacheStatistics.Stat.CACHE_WRITES_FSBUFF.toString(), CacheStatistics.getFSBuffWrites()); reporter.incrCounter(CacheableData.CACHING_COUNTER_GROUP_NAME, CacheStatistics.Stat.CACHE_WRITES_FS.toString(), CacheStatistics.getFSWrites()); reporter.incrCounter(CacheableData.CACHING_COUNTER_GROUP_NAME, CacheStatistics.Stat.CACHE_WRITES_HDFS.toString(), CacheStatistics.getHDFSWrites()); reporter.incrCounter(CacheableData.CACHING_COUNTER_GROUP_NAME, CacheStatistics.Stat.CACHE_TIME_ACQR.toString(), CacheStatistics.getAcquireRTime()); reporter.incrCounter(CacheableData.CACHING_COUNTER_GROUP_NAME, CacheStatistics.Stat.CACHE_TIME_ACQM.toString(), CacheStatistics.getAcquireMTime()); reporter.incrCounter(CacheableData.CACHING_COUNTER_GROUP_NAME, CacheStatistics.Stat.CACHE_TIME_RLS.toString(), CacheStatistics.getReleaseTime()); reporter.incrCounter(CacheableData.CACHING_COUNTER_GROUP_NAME, CacheStatistics.Stat.CACHE_TIME_EXP.toString(), CacheStatistics.getExportTime()); //reset cache statistics to prevent overlapping reporting CacheStatistics.reset(); } } public static void exportResultVariables(long workerID, LocalVariableMap vars, ArrayList<String> resultVars, OutputCollector<Writable, Writable> out) throws DMLRuntimeException, IOException { exportResultVariables(workerID, vars, resultVars, null, out); } /** * For remote MR parfor workers. * * @param workerID worker id * @param vars local variable map * @param resultVars list of result variables * @param rvarFnames ? * @param out output collector * @throws DMLRuntimeException if DMLRuntimeException occurs * @throws IOException if IOException occurs */ public static void exportResultVariables(long workerID, LocalVariableMap vars, ArrayList<String> resultVars, HashMap<String, String> rvarFnames, OutputCollector<Writable, Writable> out) throws DMLRuntimeException, IOException { //create key and value for reuse LongWritable okey = new LongWritable(workerID); Text ovalue = new Text(); //foreach result variables probe if export necessary for (String rvar : resultVars) { Data dat = vars.get(rvar); //export output variable to HDFS (see RunMRJobs) if (dat != null && dat.getDataType() == DataType.MATRIX) { MatrixObject mo = (MatrixObject) dat; if (mo.isDirty()) { if (ParForProgramBlock.ALLOW_REUSE_MR_PAR_WORKER && rvarFnames != null) { String fname = rvarFnames.get(rvar); if (fname != null) mo.setFileName(fname); //export result var (iff actually modified in parfor) mo.exportData(); //note: this is equivalent to doing it in close (currently not required because 1 Task=1Map tasks, hence only one map invocation) rvarFnames.put(rvar, mo.getFileName()); } else { //export result var (iff actually modified in parfor) mo.exportData(); //note: this is equivalent to doing it in close (currently not required because 1 Task=1Map tasks, hence only one map invocation) } //pass output vars (scalars by value, matrix by ref) to result //(only if actually exported, hence in check for dirty, otherwise potential problems in result merge) String datStr = ProgramConverter.serializeDataObject(rvar, mo); ovalue.set(datStr); out.collect(okey, ovalue); } } } } /** * For remote Spark parfor workers. This is a simplified version compared to MR. * * @param workerID worker id * @param vars local variable map * @param resultVars list of result variables * @return list of result variables * @throws DMLRuntimeException if DMLRuntimeException occurs * @throws IOException if IOException occurs */ public static ArrayList<String> exportResultVariables(long workerID, LocalVariableMap vars, ArrayList<String> resultVars) throws DMLRuntimeException, IOException { ArrayList<String> ret = new ArrayList<String>(); //foreach result variables probe if export necessary for (String rvar : resultVars) { Data dat = vars.get(rvar); //export output variable to HDFS (see RunMRJobs) if (dat != null && dat.getDataType() == DataType.MATRIX) { MatrixObject mo = (MatrixObject) dat; if (mo.isDirty()) { //export result var (iff actually modified in parfor) mo.exportData(); //pass output vars (scalars by value, matrix by ref) to result //(only if actually exported, hence in check for dirty, otherwise potential problems in result merge) ret.add(ProgramConverter.serializeDataObject(rvar, mo)); } } } return ret; } /** * Cleanup all temporary files created by this SystemML process * instance. * */ public static void cleanupWorkingDirectories() { //use the given job configuration for infrastructure analysis (see configure); //this is important for robustness w/ misconfigured classpath which also contains //core-default.xml and hence hides the actual cluster configuration; otherwise //there is missing cleanup of working directories JobConf job = ConfigurationManager.getCachedJobConf(); if (!InfrastructureAnalyzer.isLocalMode(job)) { //delete cache files CacheableData.cleanupCacheDir(); //disable caching (prevent dynamic eviction) CacheableData.disableCaching(); //cleanup working dir (e.g., of CP_FILE instructions) LocalFileUtils.cleanupWorkingDirectory(); } } public static LocalVariableMap[] getResults(List<Tuple2<Long, String>> out, Log LOG) throws DMLRuntimeException { HashMap<Long, LocalVariableMap> tmp = new HashMap<Long, LocalVariableMap>(); int countAll = 0; for (Tuple2<Long, String> entry : out) { Long key = entry._1(); String val = entry._2(); if (!tmp.containsKey(key)) tmp.put(key, new LocalVariableMap()); Object[] dat = ProgramConverter.parseDataObject(val); tmp.get(key).put((String) dat[0], (Data) dat[1]); countAll++; } if (LOG != null) { LOG.debug("Num remote worker results (before deduplication): " + countAll); LOG.debug("Num remote worker results: " + tmp.size()); } //create return array return tmp.values().toArray(new LocalVariableMap[0]); } }